Data Engineer II

4 weeks ago

Bengaluru, India Redica Systems Full time
Data Engineer II

About Us

Redica Systems is a SaaS start-up serving more than 200 customers within the life science sector, with a specific focus on Pharmaceuticals and MedTech. Embracing a hybrid model, our workforce is distributed globally, with headquarters in Pleasanton, CA.Redica's data analytics platform empowers companies to improve product quality and navigate evolving regulations. Using proprietary processes, we harness one of the industry's most comprehensive datasets, sourced from hundreds of health agencies and the Freedom of Information Act.Our customers use Redica Systems to more effectively and efficiently manage their inspection preparation, monitor their supplier quality, and perform regulatory surveillance.More information is available at redica.com.The Role

Were looking for an experienced Data Engineer II to join our team as we continue to develop the first-of-its-kind quality and regulatory intelligence (QRI) platform for the life science industry.The ideal candidate will come with experience in designing, building, and maintaining data pipelines and infrastructure maintenance while remaining hands-on in the code.Core Responsibilities

Full understanding of the technical architecture and the different subsystemsCreate the necessary infrastructure for optimal extraction, transformation, and loading (ETL) of data from various sourcesAble to work in an Agile Scrum environment, with a keen focus on delivering sustainable, high-performance, scalable, and easily maintainable enterprise solutionsPrioritize and address technical challenges, working closely with engineering managersProactively guide technical choices within your domain of expertiseRecommend and validate different ways to improve data reliability, efficiency, and qualityIdentify optimal approaches for resolving data quality or consistency issuesEnsure successful system delivery to the production environment and assist the operations and support team in resolving production issues, as necessaryHas the ability to handle the acquisition of data from a variety of sources, intelligent change monitoring, data mapping, transformations, and analysisDesign, test, and maintain data stores, databases, processing systems, and microservicesIntegrate various sub-systems or components to deliver end-to-end solutionsCollaborate with NLP/ML teams to integrate data pipeline with NLP/ML servicesAbout you

Tech Savvy : Effectively anticipates and adopts innovations in business-building technology solutions, staying up-to-date with data advancements and incorporating them into work processesManages Complexity : Actively synthesizes solutions from complex information by identifying patterns and developing effective problem-solving strategies to solve data-related problems effectivelyDecision Quality : Consistently makes good and timely decisions that propel organizational progress and maintain data integrityCollaborates : Actively engages in collaborative problem-solving by leveraging diverse perspectives and finding innovative solutions to achieve shared goals and data engineering initiativesOptimizes Work Processes : Actively seeks opportunities to enhance and streamline current work processes for managing data pipelines, ETL (Extract, Transform, Load) processes, and data warehousingDrives Results : Strives to continuously improve performance and exceed expectations to contribute to overall success and meet data-related deliverablesStrategic Mindset : Consistently demonstrates a strategic mindset by envisioning future possibilities and successfully translating them into breakthrough data strategies, contributing to the organization's long-term successEngaged:

Not only shares our values but also possesses the essential competencies needed to thrive at Redica, as outlined hereQualifications

A minimum of 4 years experience in Data Engineering3+ years of experience with an emphasis on code/system architecture and quality outputExperience designing and building data pipelines, data APIs, and ETL/ELT processesExposure to data modeling and data warehouse conceptsHands-on experience in PythonHands-on experience working with AWS Sagemaker and supporting the building of batch and real-time ML pipelines (AWS Sagemaker / MLflow)Hands-on experience setting up, configuring, and maintaining SQL and no-SQL databases (MySQL/MariaDB, PostgreSQL, MongoDB, Snowflake)Computer Science, Computer Engineering, or similar technical degreeBonus Points

Experience with the data engineering stack within AWS is a major plus (S3, Lake Formation, Lambda, Fargate, Kinesis Data Streams/Data Firehose, DynamoDB, Neptune DB)Experience with event-driven data architecturesExperience with the ELK stack is a major plus (ElasticSearch, LogStash, Kibana)

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